Fundamentals of Data Science: Prediction, Inference, Causality

3 credits · Graduate

This course provides an introduction to applied data analysis, with an emphasis on providing a conceptual framework for thinking about uncertainty from machine learning, statistical, and causal perspectives. The class involves developing an interconnected understanding across these ways of thinking. Class lectures will be supplemented by data-driven problem sets and a project. Prerequisites: multivariable calculus; probability.